activity
20162023
most citedSIENet: Spatial Information Enhancement Network for 3D Object Detection from Point Cloud

17 citations · 48 across the 16 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.CV2021

Learning Tracking Representations via Dual-Branch Fully Transformer Networks

Fei Xie, Chunyu Wang, Guangting Wang +2

We present a Siamese-like Dual-branch network based on solely Transformers for tracking. Given a template and a search image, we divide them into non-overlapping patches and extrac…

cs.CV2021

Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association

Sen Yang, Zhicheng Wang, Ze Chen +7

This paper presents a new method to solve keypoint detection and instance association by using Transformer. For bottom-up multi-person pose estimation models, they need to detect k…

cs.CV2021★ 2 cited

Video Based Fall Detection Using Human Poses

Ziwei Chen, Yiye Wang, Wankou Yang

Video based fall detection accuracy has been largely improved due to the recent progress on deep convolutional neural networks. However, there still exists some challenges, such as…

cs.CV2021

SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation

Yanjie Li, Sen Yang, Peidong Liu +5

The 2D heatmap-based approaches have dominated Human Pose Estimation (HPE) for years due to high performance. However, the long-standing quantization error problem in the 2D heatma…

cs.CV2021

TokenPose: Learning Keypoint Tokens for Human Pose Estimation

Yanjie Li, Shoukui Zhang, Zhicheng Wang +4

Human pose estimation deeply relies on visual clues and anatomical constraints between parts to locate keypoints. Most existing CNN-based methods do well in visual representation,…

cs.CV2021★ 17 cited

SIENet: Spatial Information Enhancement Network for 3D Object Detection from Point Cloud

Ziyu Li, Yuncong Yao, Zhibin Quan +2

LiDAR-based 3D object detection pushes forward an immense influence on autonomous vehicles. Due to the limitation of the intrinsic properties of LiDAR, fewer points are collected a…